Table of Contents

1 - About

In its most basic form, consistency refers to data values in one data set being consistent with values in another data set at the same point in time.

In an other form, consistency, also known as atomic consistency or linearizability, guarantees that once a write completes, all future reads will reflect that value of the write.

When all applications or thread, see the same data at the same point in time, the system is in a consistent state.

A strict definition of consistency specifies that two data values drawn from separate data sets must not conflict with each other, although consistency does not necessarily imply correctness.

Even more complicated is the notion of consistency with a set of predefined constraints. More formal consistency constraints can be encapsulated as a set of rules that specify consistency relationships between values of attributes, either across a record or message, or along all values of a single attribute.

4 - Implementation

4.1 - Database

4.2 - ETL

The best way to ensure consistency is to publish the data once.
Storing calculated fact ensures that all users and reporting applications refer to it consistently.
A single publishing run also reduces the extract tansformation load (ETL) development effort. as well the ongoing data management and disk storage burden.

5 - Example

5.1 - Rule

An example of a consistency rule verifies that within a corporate hierarchy structure, the sum of the number of employees at each site should not exceed the number of employees for the entire corporation